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A novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder for small negative samples

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High Voltage 2022年第5期7卷 925-935页

作者： Fangming Deng Wei Luo Baoquan Wei Yong Zuo Han Zeng yigang he State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong UniversityNanchangChina School of Electrical and Automation Engineering East China Jiaotong UniversityNanchangChina School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative samples.The proposed DCAE scheme combines the advantages of supervised learning and unsupervised learning.In order to reduce the high cost of training Deep Neural Networks,this paper pre-trained the Convolutional Neural Networks(CNN)through open labelled datasets.Through transferring learning,the encoder part of the traditional Convolutional Auto-Encoder was replaced by the first three layers of the CNN,and a small number of defect samples were used to fine-tune the parameters.A threshold discrimination scheme was designed to evaluate the model detection,realising the self-explosion detection of insulator by judging the residual result and abnormal score.The experimental results show that compared with the existing insulator self-explosion detection schemes,the proposed scheme can reduce the model training time by up to 40%,and the recognition accuracy can reach 97%.Moreover,this model does not need a large number of insulator labelled data and is especially suitable for small negative sample application.

关键词： scheme insulator defect

结合数据驱动与物理模型的主动配电网双时间尺度电压协调优化控制

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电工技术学报 2024年第5期39卷 1327-1339页

作者：张剑崔明建何怡刚合肥工业大学电气与自动化工程学院合肥230009 天津大学电气自动化与信息工程学院天津300072 武汉大学电气与自动化学院武汉430072

高比例电动汽车、分布式风电、光伏接入配电网,导致电压频繁地剧烈波动。传统调压设备与逆变器动作速度差异巨大,如何协调是难点问题。该文结合数据驱动与物理建模方法,提出一种配电网双时间尺度电压协调优化控制策略。针对短时间尺度(... 详细信息

高比例电动汽车、分布式风电、光伏接入配电网,导致电压频繁地剧烈波动。传统调压设备与逆变器动作速度差异巨大,如何协调是难点问题。该文结合数据驱动与物理建模方法,提出一种配电网双时间尺度电压协调优化控制策略。针对短时间尺度(min级)电压波动,以静止无功补偿器、分布式电源无功功率为决策变量,以电压二次方偏差最小为目标函数,针对平衡与不平衡配电网,基于支路潮流方程,计及物理约束构建了二次规划模型。针对长时间尺度(h级)电压波动,以电压调节器匝比、可投切电容电抗器挡位、储能系统充放电功率为动作,当前时段配电网节点功率为状态,节点电压二次方偏差为代价,构建了马尔可夫决策过程。为克服连续-离散动作空间维数灾,提出了一种基于松弛-预报-校正的深度确定性策略梯度强化学习求解算法。最后,采用IEEE 33节点平衡与123节点不平衡配电网验证了所提出方法的有效性。

关键词：智能配电网电压控制深度强化学习二次规划双时间尺度

Primal dual interior point dynamic programming for coordinated charging of electric vehicles

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Journal of Modern Power Systems and Clean Energy 2017年第6期5卷 1004-1015页

作者： Jian ZHANG yigang he Mingjian CUI Yongling LU hefei University of Technology Hefei 230009China University of Texas at Dallas RichardsonTX 75080USA State Grid Jiangsu Electric Power Company Research Institute Nanjing 211103JiangsuChina

Coordinated charging of electric vehicles(EVs)is critical to provide safe and cost effective operation of distribution systems where household single phase charging of EV could contribute to imbalance of the distribution system.To date,reported researches on optimization methods for coordinated charging aiming at minimizing power losses have the disadvantages of low calculation efficiency when applied to large systems or have not taken the voltage constraints into account.The phase component and polar coordinates power flow equations of an unbalanced distribution system are derived.Primal dual interior point dynamic programming is introduced for coordinated charging of EVs to minimize distribution system losses where charging demand,voltage and current constraints have been taken into account.The proposed optimization is evaluated using an actual 423-bus case as the test system.Results are promisingwith the proposed method having good convergence under time-efficient calculations while providing optimization of power losses,lower load variance,and improvement of voltage profile versus uncoordinated scenarios.

关键词： Electric vehicles(EVs) Coordinated charging Primal dual interior point programming Distribution system Power losses

部分分布式电源提供辅助服务的主动配电网快速鲁棒优化

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高电压技术 2024年第5期50卷 2107-2116,I0030-I0032页

作者：张剑崔明建何怡刚合肥工业大学电气与自动化工程学院合肥230009 智能电网教育部重点实验室(天津大学) 天津300072 武汉大学电气与自动化学院武汉430072

经逆变器接入配电网的分布式电源提供有功与无功辅助服务是确保配电网安全经济运行的重要手段。该文同时计及了储能系统、可投切电容电抗器、有载调压变压器分接头、静止无功补偿器调节能力,以储能与网络损耗及弃风弃光最小为目标函数,... 详细信息

经逆变器接入配电网的分布式电源提供有功与无功辅助服务是确保配电网安全经济运行的重要手段。该文同时计及了储能系统、可投切电容电抗器、有载调压变压器分接头、静止无功补偿器调节能力,以储能与网络损耗及弃风弃光最小为目标函数,计及运行约束,基于支路潮流方程构建了部分分布式电源提供辅助服务的多时段二阶段混合整数二阶锥鲁棒优化模型,提出了一种新颖的基于割平面的主、次问题二阶段直接交替迭代求解方法。不同于现有列与约束生成(columns and constraints generation,CCG)算法,该方法求解主问题时无需增加新的变量与约束条件,求解次问题时,只需针对每个时段进行求解,因此极大降低了求解复杂度与计算机内存。若求解结果不满足二阶锥精确凸松弛条件,则构建二阶段混合整数序列二阶锥鲁棒优化模型,依然能够快速求解,且可恢复出原问题的精确解。最后,采用2个仿真实例验证了所提出方法的性能。IEEE 123节点配电网的仿真结果表明,该方法计算速度是CCG算法的12~22倍。该方法可为含高比例间歇性分布式电源配电网鲁棒优化运行提供实时快速分析与求解工具,提高新能源就地消纳能力。

关键词：主动配电网分布式电源辅助服务 SOCP 鲁棒优化

基于自适应滑模观测器的中点钳位型三电平并网逆变器开关管和电流传感器故障诊断

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电工技术学报 2024年第13期39卷 4066-4078页

作者：许水清许晓凡何怡刚柴毅合肥工业大学电气与自动化工程学院合肥230009 武汉大学电气与自动化学院武汉430072 输变电装备技术全国重点实验室(重庆大学) 重庆400044

为提高中点钳位型三电平(3L-NPC)并网逆变器故障诊断的准确性和可靠性,针对其开关管开路故障和电流传感器故障,提出一种基于自适应滑模观测器的开关管开路故障和电流传感器故障同时诊断方法。该方法首先针对3L-NPC并网逆变器,设计一种... 详细信息

为提高中点钳位型三电平(3L-NPC)并网逆变器故障诊断的准确性和可靠性,针对其开关管开路故障和电流传感器故障,提出一种基于自适应滑模观测器的开关管开路故障和电流传感器故障同时诊断方法。该方法首先针对3L-NPC并网逆变器,设计一种收敛速度快且能显著抑制抖振的自适应滑模观测器来精确估计正常状态下的三相电流值;其次,利用实际电流和估计电流设计了故障检测变量;同时,利用实际三相电流之和以及估计三相电流之和来区分开关管故障和电流传感器故障;在此基础上,构造开关管故障定位变量和电流传感器故障识别变量,实现开关管开路故障的准确定位以及电流传感器故障类型的快速识别。实验结果验证了该文所提诊断算法的有效性和鲁棒性。

关键词：中点钳位型三电平(3L-NPC)并网逆变器开关管开路故障电流传感器故障自适应滑模观测器

Flower Pollination heuristics for Nonlinear Active Noise Control Systems

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Computers, Materials & Continua 2021年第4期67卷 815-834页

作者： Wasim Ullah Khan yigang he Muhammad Asif Zahoor Raja Naveed Ishtiaq Chaudhary Zeshan Aslam Khan Syed Muslim Shah School of Electrical Engineering and Automation Wuhan UniversityWuhan430072China Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan Department of Electrical Engineering International Islamic UniversityIslamabadPakistan Department of Electrical Engineering Capital University of Science and TechnologyIslamabadPakistan

In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.

关键词： Active noise control computational heuristics volterra filtering flower pollination algorithm

A Neural Network Approach for Designing 2-D FIR Filters with Arbitrary Magnitude Responses

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通讯和计算机（中英文版） 2006年第3期3卷 66-71页

作者： Xiaohua Wang yigang he Department of Electrical and Information Engineering Changsha University of Science and Technology Changsha 410077 China Department of Electrical and Information Engineering Hunan University Changsha 410082 China

In this paper, a Neural Network Approach (NNA) is presented for the design of two-dimensional (2-D) Finite-Impulse Response (FIR) filters with arbitrary magnitude responses. Its main goal is to minimize the frequency-domain error function. To illustrate the feasibility of the NNA, a Back-Propagation Neural Network (BPNN) model is chosen, and the convergence and stability of the BPNN are studied. The method avoids matrix inversion operation, and makes a very fast calculation of the filter s coefficients possible when the learning rate of the BPNN is selected suitably. The novel feature of the proposed approximation approach is that it can be used to design any kind of 2-D linear-phase FIR filters without any symmetry constraint on their magnitude-frequency responses. Several optimal design examples are given to illustrate the effectiveness of the proposed approach.

关键词： 2-D FIR Filter Neural Network Approach Convergence and Stability Optimal Design

SFG Realization of Wavelet Filter Using Switched-Current Circuits

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SFG Realization of Wavelet Filter Using Switched-Current Cir...

Universal Active Current-Mode Filter with Three Inputs and One Output Using Modified Current Conveyors

2009 IEEE 8th International Conference on ASIC(ASICON 2009)

作者： Wenshan Zhao yigang he and Yichuang Sun

A signal flow graph method for analogue implementation of wavelet transform using switched-current circuits is proposed in which the wavelet transform is synthesized by a bank of switched-current bandpass filters whose impulse responses are the mother wavelet and its dilations.To facilitate the implementation of arbitrary wavelet function,the proposed approach employs the signal flow graph methodology to design the wavelet filter.The first derivative of Gaussian wavelet is used as an example in this paper to illustrate design details.Simulation results show the feasibility of the proposed method.

关键词： Wavelet transform SFG Switched-current

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Universal Active Current-Mode Filter with Three Inputs and O...